79 lines
2.8 KiB
79 lines
2.8 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include <thrust/for_each.h>
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#include <thrust/tuple.h>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/modified_huber_loss_op.h"
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#include "paddle/fluid/platform/hostdevice.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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struct ModifiedHuberLossBackward {
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template <typename Tuple>
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HOSTDEVICE void operator()(Tuple t) const {
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auto inter_val = thrust::get<1>(t);
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auto y_val = thrust::get<2>(t);
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auto out_grad = thrust::get<3>(t);
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if (inter_val < -1) {
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thrust::get<0>(t) = -4 * (2 * y_val - 1) * out_grad;
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} else if (inter_val < 1) {
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thrust::get<0>(t) = -2 * (1 - inter_val) * (2 * y_val - 1) * out_grad;
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} else {
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thrust::get<0>(t) = 0;
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}
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}
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};
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template <typename T>
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class ModifiedHuberLossGradGPUKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* in0 = context.Input<Tensor>("Y");
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auto* in1 = context.Input<Tensor>("IntermediateVal");
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auto* in2 = context.Input<Tensor>(framework::GradVarName("Out"));
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auto* out0 = context.Output<Tensor>(framework::GradVarName("X"));
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if (out0) {
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auto counts = framework::product(in1->dims());
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auto y_ptr = thrust::device_pointer_cast(in0->data<T>());
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auto inter_val_ptr = thrust::device_pointer_cast(in1->data<T>());
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auto out_grad_ptr = thrust::device_pointer_cast(in2->data<T>());
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thrust::device_ptr<T> x_grad_ptr(
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out0->mutable_data<T>(context.GetPlace()));
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auto iter_begin = thrust::make_zip_iterator(
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thrust::make_tuple(x_grad_ptr, inter_val_ptr, y_ptr, out_grad_ptr));
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auto iter_end = thrust::make_zip_iterator(
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thrust::make_tuple(x_grad_ptr + counts, inter_val_ptr + counts,
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y_ptr + counts, out_grad_ptr + counts));
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thrust::for_each(iter_begin, iter_end, ModifiedHuberLossBackward());
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}
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_CUDA_KERNEL(
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modified_huber_loss,
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ops::ModifiedHuberLossKernel<paddle::platform::CUDADeviceContext, float>);
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REGISTER_OP_CUDA_KERNEL(modified_huber_loss_grad,
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ops::ModifiedHuberLossGradGPUKernel<float>);
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